code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride=1,
      dilation=1,
      groups=1,
      is_vd_mode=False,
      act=None,
  ):
      super(ConvBNLayer, self).__init__()
  
      self.is_vd_mode = is_vd_mode
      self._pool2d_avg = nn.AvgPool2D(
          kernel_size=2, stride=2, padding=0, ceil_mode=True
      )
      self._conv = nn.Conv2D(
          in_channels=in_channels,
          out_channels=out_channels,
          kernel_size=kernel_size,
          stride=stride,
          padding=(kernel_size - 1) // 2 if dilation == 1 else 0,
          dilation=dilation,
          groups=groups,
          bias_attr=False,
      )
  
      self._batch_norm = layers.SyncBatchNorm(out_channels)
      self._act_op = layers.Activation(act=act)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  import ppmatting
label_desc: Use image node_id 1 to create a new ConvBNLayer object from inherited base classes: nn with example: obj = ConvBNLayer(in_channels, out_channels, kernel_size, stride, dilation, groups, is_vd_mode, act)